WO2009022288A2 - Procédé de détection et d'assombrissement d'objets dans des images tramées à échelle de gris - Google Patents

Procédé de détection et d'assombrissement d'objets dans des images tramées à échelle de gris Download PDF

Info

Publication number
WO2009022288A2
WO2009022288A2 PCT/IB2008/053217 IB2008053217W WO2009022288A2 WO 2009022288 A2 WO2009022288 A2 WO 2009022288A2 IB 2008053217 W IB2008053217 W IB 2008053217W WO 2009022288 A2 WO2009022288 A2 WO 2009022288A2
Authority
WO
WIPO (PCT)
Prior art keywords
darkening
interest
grey scale
scale value
image
Prior art date
Application number
PCT/IB2008/053217
Other languages
English (en)
Other versions
WO2009022288A3 (fr
Inventor
Raoul Florent
Stephane Valente
Original Assignee
Koninklijke Philips Electronics N. V.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Koninklijke Philips Electronics N. V. filed Critical Koninklijke Philips Electronics N. V.
Priority to EP08789596A priority Critical patent/EP2188777A2/fr
Priority to CN200880103116A priority patent/CN101836234A/zh
Priority to US12/673,190 priority patent/US20120093379A1/en
Publication of WO2009022288A2 publication Critical patent/WO2009022288A2/fr
Publication of WO2009022288A3 publication Critical patent/WO2009022288A3/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T5/00—Image enhancement or restoration
    • G06T5/90—Dynamic range modification of images or parts thereof
    • G06T5/94—Dynamic range modification of images or parts thereof based on local image properties, e.g. for local contrast enhancement
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10116—X-ray image
    • G06T2207/10121—Fluoroscopy
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20092—Interactive image processing based on input by user
    • G06T2207/20101—Interactive definition of point of interest, landmark or seed
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30021—Catheter; Guide wire

Definitions

  • the invention relates to the field of fluoroscopy imaging.
  • the invention relates to a method for highlighting of intervention objects for fluoroscopy imaging, a relating imaging system, a program element and a computer readable medium.
  • wire tips and balloon/stent markers are the main landmarks used by cardiologists for navigation and precise stent placement. Because they are semi radio-opaque, the visibility of said landmarks can become quite low for several reasons.
  • the fluoroscopy pictures may be very noisy, the tips and balloon/stent markers may be located in dark areas of the image or still in the catheter tube (i.e. in a low contrast area), or masked by the vessel trace during a shot of contrast agent.
  • tips and balloon/stent markers may be masked by a vessel map overlaid onto the live picture by an automatic cardiac roadmapping system.
  • the imaging method may be used by an imaging system for
  • PTCA Percutaneous Transluminal Coronary Angioplasty
  • a description of the basic interventional procedure in this field can be found in "Algorithmic Solutions for Live Device-to-Vessel Match", J. Bredno, B. Martin-Leung & K. Eck, Proceedings of SPIE - Volume 5370 - Medical Imaging 2004: Image Processing, J. Michael Fitzpatrick, Milan Sonka, Editors, May 2004, pp. 1486-1497: "After a catheter is inserted into the vascular system at an access site, it is advanced along large vessels to the vascular structure that requires treatment. Contrast agent is injected via the catheter and [further] x-ray equipment records an angiographic sequence that shows the vessels when filled with contrast agent.
  • the diagnostic angiogram acquisitions can be repeated with varying imager geometries. Diagnosis and intervention planning are based on such diagnostic angiograms extended.
  • a flexible, partially or fully radio-opaque guidewire is advanced to the affected vascular structures (e.g. stenoses in coronaries, neurovascular aneurisms, or arterio -venous malformations). Fluoroscopic low-dose x-ray surveillance visualizes the guidewire covered and allows for the hand-eye-coordination of the interventionalist while advancing the guidewire.
  • the guidewire serves as rail to deliver interventional devices (e.g. balloons for dilation and stent delivery, detachable coils for aneurysm clotting).
  • the delivery and deployment of the interventional devices is also fluoroscopy-controlled.”
  • the vessel structure itself is not visible during the intervention as it is not radio-opaque. Consequently, the navigation and precise positioning of guidewire and interventional devices may be tedious, time- consuming, and requires additional contrast agent bursts to clarify the position of the devices relative to the relevant vessels.”
  • a method for highlighting an object of interest in a first raster image of grey scale value pixels comprising the steps of selecting of the object of interest in the raster image and darkening the object of interest with a grey scale value using a predetermined darkening strength parameter.
  • One feature of the embodiment may be to provide an operators with an augmented visibility of the objects of interest (catheters, wire guide tips, balloon/stent markers) by smoothly darkening them. Since X-Ray images are in grey levels and objects of interest are semi-opaque, a controlled darkening operation produces a natural-looking result, while not being gaze-catching. Thus, an always possible misdetection of objects may not lead to disturbing artefacts.
  • the darkening operation can be adaptive to the presence of contrast agent or local image characteristics.
  • a method for highlighting an object of interest in a first raster image of grey scale value pixels comprises the steps: detecting of the object of interest in the raster image, obtaining a darkening grey scale value, and darkening the object of interest with the darkening grey scale value.
  • a plurality of different or equal darkening grey scale values are obtained and used for darkening a plurality of object pixels or all object pixels of the detected objects.
  • the darkening grey scale value is obtained from a predetermined darkening strength parameter.
  • the method further comprises the step of obtaining detection information from said detecting of the object of interest in the raster image.
  • the detection process might also produces detection information such as a confidence map that contains, for every detected pixel, a value indicating how confident the detection algorithm is of being correct.
  • the detection process often consists in thresholding an enhanced image where the enhancement value can directly be used to qualify the detection information, e.g. the degree of detection confidence.
  • the detection information is configured as one of the group consisting of data of localisation, data of topology, data of local or global confident measurement.
  • the grey scale value is obtained from the obtained detection information.
  • the grey scale value is weighted by the detection information.
  • the darkening grey scale value is obtained from a predetermined darkening strength parameter and the detection information.
  • an imaging system for examination of an object of interest comprises a detector unit, adapted to detect the object of interest in a raster image and a picture composer, adapted to darken the object of interest with a grey scale value using a predetermined darkening strength parameter.
  • the imaging system may be implemented into automatic cardiac road mapping systems or used for any fluoroscopy application.
  • the image system may comprise a processor unit, adapted to determine the darkening strength parameter.
  • the system may comprise a local image analyser or/and a contrast agent monitoring device.
  • a computer- readable medium in which a computer program for highlighting an object of interest is stored which, when being executed by a processor, is adapted to carry out the steps of detecting of the object of interest in the raster image, determining a darkening strength parameter for the object of interest, and darkening the object of interest with a grey scale value using the determined darkening strength parameter.
  • a program element for highlighting an object of interest which, when being executed by a processor, is adapted to carry out the steps of detecting of the object of interest in the raster image, determining a darkening strength parameter for the object of interest and darkening the object of interest with a grey scale value using the determined darkening strength parameter.
  • the method further comprises the step of generating object pixel data of the detected object in an object mask image.
  • the method further comprises the steps of monitoring object-surrounding presence and/or concentration of contrast agent and determining the darkening strength parameter using the monitored presence and/or concentration values of contrast agent.
  • the method further comprises the steps of acquiring object-surrounding local image area properties, and analysing the acquired local image area properties, determining the darkening strength parameter using the acquired image area properties.
  • the local image area properties include the mean grey scale value, determined from grey scale values of a plurality of object surrounding pixel, and/or the mean contrast value of a plurality of object surrounding pixel.
  • the darkening strength parameter is used globally for the darkening of the object of interest.
  • a plurality of different grey scale values using the predetermined darkening strength is used for the darkening of the object of interest.
  • Yet another aspect of the method may be that the method further comprises the steps of composing a final picture, using the first raster image, the determined darkening strength parameter and the generated object mask image.
  • the object of interest is an artificial device used for intra-coronary surveillance
  • the object of interest is configured as one of the group consisting of a catheter, a wire guide tip, a balloon marker and a stent marker.
  • a local image analyzer and a contrast agent monitor are both optional devices of the imaging system .
  • the system may just comprise an object detector and a picture composer.
  • the object detection and mask composition can be carried out simultaneous, and not only sequential in another aspect. Further the presence of object masks/maps are not mandatory, a composer device of the imaging system could take as input any data representing the location and/or appearance of particular objects, like chained lists of pixels, splines, coordinates of markers, to darken/highlighting the objects accordingly. Further, different darkening algorithms can be used.
  • Fig. 1 shows four cardio logic grey scale X-ray images of a patient with a visible wire tip in a catheter tube.
  • Fig. 2 shows four cardio logic grey scale X-ray images of a patient, wherein the a visible wire tip is overlaid in white.
  • Fig. 3 shows four cardio logic grey scale X-ray images of a patient wherein the tip is not correctly segmented.
  • Fig. 4 shows a schematically diagram of one embodiment of the claimed imaging method
  • Fig. 5 shows four images in different status according to one embodiment of the imaging method.
  • Fig. 6 shows eight images according to an overlay scheme.
  • the left column shows different grey scale X-ray live images, the right column shows the said live images after darkening of an object of interest.
  • Fig. 7 shows another schematically diagram of one embodiment of the claimed imaging method.
  • Fig. 1 Four different cardio logic grey scale X-ray live images of a patient with a visible wire tip in a catheter tube are shown in Fig. 1. In the shown examples the visibility of the wire tip could obviously be improved. The first row shows the tip in the catheter tube on the right side of each image, the last one shows the tip during a shot of contrast agent.
  • the shown low visibility problem may result in longer visual accommodation time for the cardiologists, requiring longer X-Ray expositions.
  • One solution could consist in using coloured overlays on the live X-Ray image to highlight the objects of interest, as shown in the next four images of Fig. 2 where the tip is overlaid in white on the right column.
  • the shown solution can be pretty effective to help the physician locate the objects of interest.
  • it suffers from two limitations. Firstly, it does not look natural or familiar to the cardiologists.
  • the live images from the left each shows a wire tip, which is on the right highlighted by a white overlay.
  • the first row is a false alarm
  • the second one a bad segmentation.
  • the segmented portion of the images on the left may not be consistent from one frame to the other in the image video sequence. It is therefore highly desirable to be able to increase the visibility of opaque objects of interest such as wire tips in a more natural manner that may also limits the annoyance of object misdetections.
  • Fig. 4 shows a diagram according to one embodiment of an imaging method.
  • the imaging method may apply the following steps.
  • the objects of interest in a live raster image 100 of grey scale value pixels are detected from a detector unit, here a intra-coronary devices detector 200. Their location is indicated by an object pixel map 400.
  • the local picture properties around the object of interest, e.g. a tip, are analyzed by an analyser 300 , taking the current original image 100 and the object map 400 as inputs.
  • the output is the darkening strength parameter(s) 500.
  • an image composer 600 processes the object map 400 and uses it to darken the objects in the original picture 100 with the required strength.
  • Object Detection For the purpose of object detection, techniques such as multiscale enhancement of dark objects and thresholding as described in "Multiscale Vessel Enhancement and Filtering", A. Frangi et al., Lecture Notes Computer Science, vol. 1496, pp 130-137, 1998, can be used.
  • the live picture 100 is fed into an object detector 200, which produces a map (or a mask) image 400 for each type of object (catheter, wire guide tip, balloon/stent markers), where pixels indicate the presence or absence of the considered object.
  • Fig. 5 first row, shows a live fluoroscopy image on the left, along with the corresponding mask for the tip object (right). Analysis of image properties
  • the object mask is fed into the local image analyzer 300 which computes the properties of the pixels in the neighbourhood of the object of interest/tip. Such properties may include the local mean luminance or the local contrast measured at the tip, to better adapt the darkening operation to the human visual system.
  • the analyser 300 determines the strength of the darkening operation for the picture composer 600, which can be in the form of a single parameter applied globally for the darkening of the tip pixels, or a strength pixel map representing parameters applied individually to each of the pixels under the tip and its neighbourhood.
  • the tip mask shown in the upper right of an live image which is shown in the upper left of Fig. 5 is Gaussian- filtered, to obtain a smooth image of the tip shape, shown in the lower right.
  • the Gaussian filter has been applied to the image in order to define the darkening grey scale value/darkening for each pixel.
  • This embodiment shows that that darkening might depend not from a local analysis of the image.
  • the said smoothed tip image is subtracted to the original picture to obtain a final image (Fig. 4, 700) shown in the lower left of Fig. 5.
  • the darkening grey scale values might be computed from detection information (localisation, topology, confidence measurement, ...) and/or local (in the vicinity of the detected objects ) or global measurements in the image.
  • Fig. 6 shows some examples of the described overlay scheme.
  • the right image column are live images before the overlay, the left column shows the images with darkened tips. It can be seen in the last two rows of Fig. 6 that object misdetections are not as disturbing as with white overlays, shown in Fig. 3.
  • the darkening of the object of interest can be made globally adaptive to contrast agent shots in vessels instead of being locally adaptive to image properties.
  • the local image analyzer is replaced by a block 800 that monitors the presence and/or amount of contrast agent in the vessels. It can determine the proper strength of the darkening operation performed on the tip object to make up for the darkening of the vessels.
  • the objects of interest in a live raster image 100 of grey scale value pixels are detected from a detector unit, here as in Fig.4 a intra-coronary devices detector 200.
  • the location of the object pixels is indicated by an object pixel mask 900.
  • Device 800 monitors the presence and/or amount of contrast agent in the vessels, and takes the current original image 100 and the object mask 900 as inputs. The output is the darkening strength parameter(s) 500. Lastly, an image composer 600 processes the object mask 900 and uses it to darken the objects in the original picture 100 with the required strength in the final composition image 700.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Radiology & Medical Imaging (AREA)
  • Quality & Reliability (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Apparatus For Radiation Diagnosis (AREA)

Abstract

Selon l'invention, des pointes de fil et marqueurs de ballonnet/ endoprothèse vasculaire sont les points de repère principaux utilisés par les cardiologues pour une navigation et un placement d'endoprothèse vasculaire précis sous une surveillance par fluoroscopie à rayons X. Ces dispositifs intra-coronaires sont semi-radio-opaques. Dans certaines situations, leur visibilité peut être extrêmement faible. Ce qui est revendiqué peut aider les cardiologues à détecter les objets et à les assombrir sur l'image à rayons X en direct pour augmenter leur visibilité. Le traitement d'assombrissement prend en compte des propriétés d'image autour des objets ou des informations de détection afin d'obtenir une meilleure amélioration de contraste. Cette technique évite également l'introduction d'artefacts gênants lorsque la détection d'objet échoue.
PCT/IB2008/053217 2007-08-16 2008-08-12 Procédé de détection et d'assombrissement d'objets dans des images tramées à échelle de gris WO2009022288A2 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
EP08789596A EP2188777A2 (fr) 2007-08-16 2008-08-12 Procédé de détection et d'assombrissement d'objets dans des images tramées à échelle de gris
CN200880103116A CN101836234A (zh) 2007-08-16 2008-08-12 灰度光栅图像中的目标的探测和暗化方法
US12/673,190 US20120093379A1 (en) 2007-08-16 2008-08-12 Detecting and darkening method of objects in grey-acale raster images

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
EP07114468.7 2007-08-16
EP07114468 2007-08-16

Publications (2)

Publication Number Publication Date
WO2009022288A2 true WO2009022288A2 (fr) 2009-02-19
WO2009022288A3 WO2009022288A3 (fr) 2009-06-04

Family

ID=40351248

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/IB2008/053217 WO2009022288A2 (fr) 2007-08-16 2008-08-12 Procédé de détection et d'assombrissement d'objets dans des images tramées à échelle de gris

Country Status (4)

Country Link
US (1) US20120093379A1 (fr)
EP (1) EP2188777A2 (fr)
CN (1) CN101836234A (fr)
WO (1) WO2009022288A2 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011039673A1 (fr) 2009-09-29 2011-04-07 Koninklijke Philips Electronics N.V. Cartographie vasculaire

Families Citing this family (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US10716528B2 (en) 2007-03-08 2020-07-21 Sync-Rx, Ltd. Automatic display of previously-acquired endoluminal images
US11064964B2 (en) 2007-03-08 2021-07-20 Sync-Rx, Ltd Determining a characteristic of a lumen by measuring velocity of a contrast agent
JP5639764B2 (ja) 2007-03-08 2014-12-10 シンク−アールエックス，リミティド 運動する器官と共に使用するイメージング及びツール
US11197651B2 (en) 2007-03-08 2021-12-14 Sync-Rx, Ltd. Identification and presentation of device-to-vessel relative motion
US8781193B2 (en) 2007-03-08 2014-07-15 Sync-Rx, Ltd. Automatic quantitative vessel analysis
US9375164B2 (en) 2007-03-08 2016-06-28 Sync-Rx, Ltd. Co-use of endoluminal data and extraluminal imaging
US9629571B2 (en) 2007-03-08 2017-04-25 Sync-Rx, Ltd. Co-use of endoluminal data and extraluminal imaging
US9968256B2 (en) 2007-03-08 2018-05-15 Sync-Rx Ltd. Automatic identification of a tool
US9305334B2 (en) * 2007-03-08 2016-04-05 Sync-Rx, Ltd. Luminal background cleaning
US9974509B2 (en) 2008-11-18 2018-05-22 Sync-Rx Ltd. Image super enhancement
US11064903B2 (en) 2008-11-18 2021-07-20 Sync-Rx, Ltd Apparatus and methods for mapping a sequence of images to a roadmap image
US10362962B2 (en) 2008-11-18 2019-07-30 Synx-Rx, Ltd. Accounting for skipped imaging locations during movement of an endoluminal imaging probe
EP2863802B1 (fr) 2012-06-26 2020-11-04 Sync-RX, Ltd. Traitement d'image lié au flux dans les organes luminaux
US9082158B2 (en) 2012-09-19 2015-07-14 Siemens Aktiengesellschaft Method and system for real time stent enhancement on live 2D fluoroscopic scene
US20150187329A1 (en) * 2014-01-02 2015-07-02 GroupeSTAHL Method and system for implementing flexible color schemes in a raster image
EP3427668B1 (fr) * 2017-07-11 2019-07-10 Siemens Healthcare GmbH Adaptation d'intensité automatisé dans la fluoroscopie

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5289373A (en) * 1991-11-29 1994-02-22 General Electric Company Method and apparatus for real-time tracking of catheter guide wires in fluoroscopic images during interventional radiological procedures
WO2001031583A1 (fr) * 1999-10-26 2001-05-03 Koninklijke Philips Electronics N.V. Procede de traitement d'images, appareil et systeme de reduction de bruits dans une sequence d'image respresentant une structure filiforme
JP2003024311A (ja) * 2001-07-17 2003-01-28 Hitachi Medical Corp 画像処理装置
WO2005104951A1 (fr) * 2004-04-29 2005-11-10 Koninklijke Philips Electronics N.V. Systeme de vision permettant de controler des angiogrammes ptca
US20070071296A1 (en) * 2005-09-28 2007-03-29 Ryosuke Nonaka Radiographic image processing apparatus for processing radiographic image taken with radiation, method of radiographic image processing, and computer program product therefor

Family Cites Families (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8165360B2 (en) * 2006-12-06 2012-04-24 Siemens Medical Solutions Usa, Inc. X-ray identification of interventional tools
DE102007019328A1 (de) * 2007-04-24 2008-11-06 Siemens Ag Verfahren zur hochauflösenden Darstellung filigraner Gefäßimplantate in angiographischen Aufnahmen

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5289373A (en) * 1991-11-29 1994-02-22 General Electric Company Method and apparatus for real-time tracking of catheter guide wires in fluoroscopic images during interventional radiological procedures
WO2001031583A1 (fr) * 1999-10-26 2001-05-03 Koninklijke Philips Electronics N.V. Procede de traitement d'images, appareil et systeme de reduction de bruits dans une sequence d'image respresentant une structure filiforme
JP2003024311A (ja) * 2001-07-17 2003-01-28 Hitachi Medical Corp 画像処理装置
WO2005104951A1 (fr) * 2004-04-29 2005-11-10 Koninklijke Philips Electronics N.V. Systeme de vision permettant de controler des angiogrammes ptca
US20070071296A1 (en) * 2005-09-28 2007-03-29 Ryosuke Nonaka Radiographic image processing apparatus for processing radiographic image taken with radiation, method of radiographic image processing, and computer program product therefor

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
AUFRICHTIG R ET AL: "X-RAY FLUOROSCOPY SPATIO-TEMPORAL FILTERING WITH OBJECT DETECTION" IEEE TRANSACTIONS ON MEDICAL IMAGING, IEEE SERVICE CENTER, PISCATAWAY, NJ, US, vol. 14, no. 4, 1 December 1995 (1995-12-01), pages 733-746, XP000548591 ISSN: 0278-0062 *
BREDNO JOERG; MARTIN-LEUNG BARBARA; ECK KAI: "Software architecture for live enhancement of medical images" PROCEEDINGS OF SPIE - THE INTERNATIONAL SOCIETY FOR OPTICAL ENGINEERING - REAL-TIME IMAGING VIII 2004 SPIE US, vol. 5297, 22 January 2004 (2004-01-22), pages 122-133, XP002521528 Real-Time Imaging VIII 20040120 to 20040122 San Jose, CA *

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2011039673A1 (fr) 2009-09-29 2011-04-07 Koninklijke Philips Electronics N.V. Cartographie vasculaire
US9095308B2 (en) 2009-09-29 2015-08-04 Koninklijke Philips N.V. Vascular roadmapping
RU2570758C2 (ru) * 2009-09-29 2015-12-10 Конинклейке Филипс Электроникс Н.В. Картирование сосудов

Also Published As

Publication number Publication date
EP2188777A2 (fr) 2010-05-26
US20120093379A1 (en) 2012-04-19
WO2009022288A3 (fr) 2009-06-04
CN101836234A (zh) 2010-09-15

Similar Documents

Publication Publication Date Title
US20120093379A1 (en) Detecting and darkening method of objects in grey-acale raster images
US9095308B2 (en) Vascular roadmapping
US9545237B2 (en) Method and device for recording a vascular struture during intervention
JP4426297B2 (ja) ノイズの多い画像中の構造を強調する医用ビューイングシステム及び方法
US9042628B2 (en) 3D-originated cardiac roadmapping
RU2710668C2 (ru) Цифровая субтракционная ангиография с аппаратной компенсацией движения
EP2338140B1 (fr) Amplification combinée dispositif et anatomie
US20100061603A1 (en) Spatially varying 2d image processing based on 3d image data
KR20080043774A (ko) 블라인드 디콘볼루션으로 노이즈 이미지에서의 구조를공간적으로 향상시키는 시스템 및 방법
JP5848858B2 (ja) Ｘ線イメージングにおける骨組織抑制
JP2019162451A (ja) 自動的な動き検出
JP6750425B2 (ja) 放射線画像処理装置および放射線画像処理方法
US20200305828A1 (en) Radiation Image Processing Apparatus and Radiation Image Processing Method
Condurache et al. Fast detection and processing of arbitrary contrast agent injections in coronary angiography and fluoroscopy
CN108024775B (zh) 再血管化定位和前后量化冠状动脉血管造影
CN115804614A (zh) 用于运动稳定的临床工具跟踪和可视化的方法及系统
CN106714689B (zh) 对比剂到达检测
DE102021213995A1 (de) Bereitstellen eines Ergebnisdatensatzes

Legal Events

Date Code Title Description
WWE Wipo information: entry into national phase

Ref document number: 200880103116.0

Country of ref document: CN

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 08789596

Country of ref document: EP

Kind code of ref document: A2

WWE Wipo information: entry into national phase

Ref document number: 2008789596

Country of ref document: EP

WWE Wipo information: entry into national phase

Ref document number: 12673190

Country of ref document: US

NENP Non-entry into the national phase

Ref country code: DE

WWE Wipo information: entry into national phase

Ref document number: 1278/CHENP/2010

Country of ref document: IN